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HomeComputingArtificial IntelligenceDeep Learning in AI Development: How It Works and Why to Implement

Deep Learning in AI Development: How It Works and Why to Implement

AI Development
Image by iuriimotov on Freepik

Programs that run machine learning algorithms are often called intelligent, even though most do not learn without human intervention. Instead, deep learning can do the job on its own. Let’s find out what it is, how it works, and what this technology can give you.

What Is Deep Learning?

Deep learning is a machine learning type that uses massive data sets and neural network architectures. In traditional ML, the developer defines a set of functions and their parameters that transform the input data in a certain way to achieve a desired outcome. Deep learning neural networks can do it on their own (‘learn’). The artificial intelligence experts tweak general parameters and provide the program with large amounts of training data. The model uses this information to build a desired set of functions to perform the task.

How Deep Learning Works

The architecture of a neural network consists of several levels of interconnected nodes (functions). Each layer performs some transformation of the input data until the output layer is reached, proving some result of the analysis. Then, the process is repeated, considering how far off the result was from the desired one. With each iteration, the neural network becomes more accurate and, usually, complex.

Deep Learning Use Cases

Deep learning algorithms are perfect for operating significant volumes of unstructured data and other complex tasks.

Image Recognition

Deep learning helps find and identify individual objects in the image. For example, Facebook uses technology to recognize human faces in group photos.

Image Classification

Do you want to tag images or define categories based on their content? Deep learning will help identify objects in the sensors of a self-driving car or tag pictures in social networks.

Speech Recognition

Simplify the transcription of spoken statements into written text. This allows you to quickly decipher and translate speech and recognize voice commands by smart home systems.

Natural Language Processing

Understanding human language helps summarize articles, analyze sentiment, create human-like text in chatbots, etc.

Translation

You have experienced a convenient automatic translation of web pages or documents into the desired language.

Recommendation Engines

Giants like Amazon and Netflix offer recommendations based on experience. Deep learning mechanisms make it possible to improve suggestions and find hidden correlations invisible to the human eye. And they are constantly learning and improving their delivery.

Analytics

Deep learning models work with large databases, revealing insights and patterns. This allows you to analyze customer behaviour, catch up on trends, and even detect fraud.

Forecasting

Need to predict future trends, behaviour, or profits? Use the power of deep learning with time series prediction, sequential data modelling, multivariate forecasting, uncertainty estimation, and other ways.

Do you want to implement deep learning in your workflow? Contact S-PRO to discuss the options.

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